1435 research outputs found
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Dynamic smoothness parameter for fast gradient methods
No full textWe present and computationally evaluate a variant of the fast gradient method by Nesterov that is capable of exploiting information, even if approximate, about the optimal value of the problem. This information is available in some applications, among which the computation of bounds for hard integer programs. We show that dynamically changing the smoothness parameter of the algorithm using this information results in a better convergence profile of the algorithm in practice
Different Decomposition Strategies to Solve Stochastic Hydrothermal Unit Commitment Problems
No full textSolving very-large-scale optimization problems frequently require to decompose them in smaller subproblems, that are iteratively solved to produce useful information. One such approach is the Lagrangian Relaxation (LR), a broad range technique that leads to many different decomposition schemes. The LR supplies a lower bound of the objective function and useful information for heuristics aimed at constructing feasible primal solutions. In this paper, we compare the main LR strategies used so far for Stochastic Hydrothermal Unit Commitment problems, where uncertainty mainly concerns water availability in reservoirs and demand (weather conditions). This problem is customarily modeled as a two-stage mixed-integer optimization problem. We compare different decomposition strategies (unit and scenario schemes) in terms of quality of produced lower bound and running time. The schemes are assessed with various hydrothermal systems, considering different configuration of power plants, in terms of capacity and number of units
Sermoni "In festo Sancti Francisci" ms. Vaticano Borghesiano 138
Full text linkL'articolo è la prima edizione di quattro sermoni in festo sancti Francisci presenti nel manoscritto n. 138 del Fondo Borghesiano della Biblioteca Apostolica Vaticana. Il codice, che faceva parte della biblioteca privata del pontefice Giovanni XXII ad Avignone, ci trasmette un sermonario compilato con materiali raccolti entro il 1317 da un anonimo francescano di area marsigliese.
I quattro sermoni editi ritraggono san Francesco come un exemplum da seguire da parte dei confratelli secondo un modello agiografico di santità provata e garantita dalle stimmate, tema che torna più volte in quasi tutti i sermoni della raccolta dedicati al santo. E' un Francesco ormai conosciuto tramite la mediazione di Bonaventura, una figura che crea l'identità francescana come identità di gruppo
Differentiated oligopolistic markets with concave cost functions via Ky Fan inequalities
No full textA model for Nash-Cournot oligopolistic markets with concave cost functions and a differentiated commodity is analysed. Equilibrium states are characterized through Ky Fan inequalities. Relying on the minimization of a suitable merit function, a general algorithmic scheme for solving them is provided. Two concrete algorithms are therefore designed that converge under suitable convexity and monotonicity assumptions. The results of preliminary numerical tests on randomly generated markets are also reported
Human-driven application management at the Edge
No full textThe design and management of Edge systems will proactively involve human intelligence at the Edge, according to a human-driven approach that increases productivity and improves usability. Due to its ubiquity and heterogeneity, the Edge will give to application administrators a more decisional role in application deployment and resource management. Final decisions on where to distribute application components should be informedly taken by them during the entire application lifecycle, accounting for compliance to QoS requirements.
As a first step, this requires devising new tools that suitably abstract heterogeneity of edge systems, permit simulating different runtime scenarios and ease human-driven management of such systems by providing meaningful evaluation metrics. In this article, we discuss how human decision-making can be supported to solve QoS-aware management related challenges for Edge computing
Improving the Approximated Projected Perspective Reformulation by Dual Information
No full textWe propose an improvement of the Approximated Projected Perspective Reformulation (AP^2R) of [Frangioni, Furini, Gentile, Computational Optimization and Applications, 2016] for the case in which constraints linking the binary variables exist. The new approach requires to solve the Perspective Reformulation (PR) once, and then use the corresponding dual information to reformulate the problem prior to applying AP^2R, thereby combining the root bound quality of the PR with the reduced relaxation computing time of AP^$R. Computational results for the cardinality-constrained Mean-Variance portfolio optimization problem show that the new approach is competitive with state-of-the-art ones
Decision Point Analysis on Learning Process Models in FLOSS mailing Archives
No full textAbstract. Numerous studies continue to explore the potential of social
interactions between people in Free/Libre Open Source Software
(FLOSS) environments. While the dynamics of interactions in these environments
can be understood from different perspectives, we put a particular
focus on any interactions resulting in knowledge transfer and acquisition.
As learning platforms, FLOSS communities provide immense
opportunities for improving software engineering skills. People who engage
in FLOSS activities both acquire and improve their software development
skills. For this reason, it is very helpful to understand how these
learning interactions occur. In this paper, we make use of the decision
miner in process mining to conduct our analysis. The purpose of such
an endeavour is twofold. Firstly, we provide empirical insights into how
people learn while exchanging emails in FLOSS mailing archives. Lastly,
we go a step further by providing insights behind the motivation into
learning participants' decisions on their learning paths
Mining Educational Social Network Structures from FLOSS Repositories
No full textFLOSS environments have been proved to provide an interesting
learning platform for software engineers. Research suggests that
people partaking in both technical and non-technical activities in FLOSS
prjects are more likely to positively improve their software engineering
skills. To this end, there are propositions to involve computer science and
software engineering students in formal higher institutions of learning,
in participating in FLOSS projects in order to give them an opportunity
to develop their programming capacity by working on real-life projects.
While some empirical studies have been conducted to provide some lights
on learning processes in FLOSS environments, there is limited or no work
done pertaining to understanding social structures during this process of
knowledge transfer and acquisition. In this paper, we make use of social
network analysis techniques in order to provide insights related to
the emerging of social structures from FLOSS repositories from an educational
point of view. We hope that these educational structures will
enhance both the understanding with regards to how learning occurs in
these communities and especially, the frequency of participants' involvement
that culminates into learning
Decision Point Analysis on Learning Process Models in FLOSS mailing Archives
No full textAbstract. Numerous studies continue to explore the potential of social
interactions between people in Free/Libre Open Source Software
(FLOSS) environments. While the dynamics of interactions in these environments
can be understood from different perspectives, we put a particular
focus on any interactions resulting in knowledge transfer and acquisition.
As learning platforms, FLOSS communities provide immense
opportunities for improving software engineering skills. People who engage
in FLOSS activities both acquire and improve their software development
skills. For this reason, it is very helpful to understand how these
learning interactions occur. In this paper, we make use of the decision
miner in process mining to conduct our analysis. The purpose of such
an endeavour is twofold. Firstly, we provide empirical insights into how
people learn while exchanging emails in FLOSS mailing archives. Lastly,
we go a step further by providing insights behind the motivation into
learning participants' decisions on their learning paths
Incremental bundle methods using upper models
No full textWe propose a family of proximal bundle methods for minimizing sum-structured convex nondifferentiable functions which require two slightly uncommon assumptions, that are satisfied in many relevant applications: Lipschitz continuity of the functions and oracles which also produce upper estimates on the function values. In exchange, the methods: i) use upper models of the functions that allow to estimate function values at points where the oracle has not been called; ii) provide the oracles with more information about when the function computation can be interrupted, possibly diminishing their cost; iii) allow to skip oracle calls entirely for some of the component functions, not only at ``null steps'' but also at ``serious steps''; iv) provide explicit and reliable a-posteriori estimates of the quality of the obtained solutions; v) work with all possible combinations of different assumptions on the oracles. We also discuss introduction of constraints (or, more generally, of easy components) and use of (partly) aggregated models